KEEN TO HELP? MANAGERS' IMPLICIT PERSON THEORIES AND THEIR SUBSEQUENT EMPLOYEE COACHING
Bibliographic record
Abstract
Although coaching can facilitate employee development and performance, the stark reality is that managers often differ substantially in their inclination to coach their subordinates. To address this issue, we draw from and build upon a body of social psychology research that finds that implicit person theories (IPTs) about the malleability of personal attributes (e.g., personality and ability) affect one's willingness to help others. Specifically, individuals holding an “entity theory” that human attributes are innate and unalterable are disinclined to invest in helping others to develop and improve, relative to individuals who hold the “incremental theory” that personal attributes can be developed. Three studies examined how managers' IPTs influence the extent of their employee coaching. First, a longitudinal field study found that managers' IPTs predicted employee evaluations of their subsequent employee coaching. This finding was replicated in a second field study. Third, an experimental study found that using self‐persuasion principles to induce incremental IPTs increased entity theorist managers' willingness to coach a poor performing employee, as well as the quantity and quality of their performance improvement suggestions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".